MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING

Detalhes bibliográficos
Autor(a) principal: Noronha,Rafael H. F.
Data de Publicação: 2018
Outros Autores: Zerbato,Cristiano, Silva,Rouverson P. da, Ormond,Antonio T. S., Oliveira,Mailson F. de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia Agrícola
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200244
Resumo: ABSTRACT The peanuts harvesting mechanization is affected by the soil physical characteristics and it may increase the losses due to the production of pods in subsurface. The objective of the experiment was to identify the clusters through multivariate exploratory approaches from similarity in six soil textures (very clayey, clayey, silty clayey loam, clayey loam, sandy loam and sandy) in the state of São Paulo, Brazil, determining the main agronomic variables that most influenced the clustering division to assist the decision-making process in peanuts mechanized harvesting. The data were analyzed by the multivariate exploratory that is performed to simplify the description of a set of interrelated variables, using: yield, maturity, soil and pod moisture content, windrow width and height, visible and invisible digging losses, and gathering losses, as agronomic indicators of quality. The low and high clay content were grouped into clusters I and III, respectively, according to the agronomic traits of the peanut crop. The principal components analysis (PC) allowed a single distribution of accesses since only two eigenvalues were higher than “one”: the highest eigenvalues of 4.51 and 1.79, resulted in a Biplot that explained 70% of the original variability, 50.11% and 19.89% of which in the PC1 and PC2, respectively. The multivariate analysis indicated that high peanut yields in soils with low clay are correlated with the losses during the peanut mechanized harvesting operation.
id SBEA-1_4b1b60ab8a57224615fe6660d440b975
oai_identifier_str oai:scielo:S0100-69162018000200244
network_acronym_str SBEA-1
network_name_str Engenharia Agrícola
repository_id_str
spelling MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTINGsoil textural classesArachis hypogaea L.principal components analysisABSTRACT The peanuts harvesting mechanization is affected by the soil physical characteristics and it may increase the losses due to the production of pods in subsurface. The objective of the experiment was to identify the clusters through multivariate exploratory approaches from similarity in six soil textures (very clayey, clayey, silty clayey loam, clayey loam, sandy loam and sandy) in the state of São Paulo, Brazil, determining the main agronomic variables that most influenced the clustering division to assist the decision-making process in peanuts mechanized harvesting. The data were analyzed by the multivariate exploratory that is performed to simplify the description of a set of interrelated variables, using: yield, maturity, soil and pod moisture content, windrow width and height, visible and invisible digging losses, and gathering losses, as agronomic indicators of quality. The low and high clay content were grouped into clusters I and III, respectively, according to the agronomic traits of the peanut crop. The principal components analysis (PC) allowed a single distribution of accesses since only two eigenvalues were higher than “one”: the highest eigenvalues of 4.51 and 1.79, resulted in a Biplot that explained 70% of the original variability, 50.11% and 19.89% of which in the PC1 and PC2, respectively. The multivariate analysis indicated that high peanut yields in soils with low clay are correlated with the losses during the peanut mechanized harvesting operation.Associação Brasileira de Engenharia Agrícola2018-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200244Engenharia Agrícola v.38 n.2 2018reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-eng.agric.v38n2p244-250/2018info:eu-repo/semantics/openAccessNoronha,Rafael H. F.Zerbato,CristianoSilva,Rouverson P. daOrmond,Antonio T. S.Oliveira,Mailson F. deeng2018-05-29T00:00:00Zoai:scielo:S0100-69162018000200244Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2018-05-29T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false
dc.title.none.fl_str_mv MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
title MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
spellingShingle MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
Noronha,Rafael H. F.
soil textural classes
Arachis hypogaea L.
principal components analysis
title_short MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
title_full MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
title_fullStr MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
title_full_unstemmed MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
title_sort MULTIVARIATE ANALYSIS OF PEANUT MECHANIZED HARVESTING
author Noronha,Rafael H. F.
author_facet Noronha,Rafael H. F.
Zerbato,Cristiano
Silva,Rouverson P. da
Ormond,Antonio T. S.
Oliveira,Mailson F. de
author_role author
author2 Zerbato,Cristiano
Silva,Rouverson P. da
Ormond,Antonio T. S.
Oliveira,Mailson F. de
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Noronha,Rafael H. F.
Zerbato,Cristiano
Silva,Rouverson P. da
Ormond,Antonio T. S.
Oliveira,Mailson F. de
dc.subject.por.fl_str_mv soil textural classes
Arachis hypogaea L.
principal components analysis
topic soil textural classes
Arachis hypogaea L.
principal components analysis
description ABSTRACT The peanuts harvesting mechanization is affected by the soil physical characteristics and it may increase the losses due to the production of pods in subsurface. The objective of the experiment was to identify the clusters through multivariate exploratory approaches from similarity in six soil textures (very clayey, clayey, silty clayey loam, clayey loam, sandy loam and sandy) in the state of São Paulo, Brazil, determining the main agronomic variables that most influenced the clustering division to assist the decision-making process in peanuts mechanized harvesting. The data were analyzed by the multivariate exploratory that is performed to simplify the description of a set of interrelated variables, using: yield, maturity, soil and pod moisture content, windrow width and height, visible and invisible digging losses, and gathering losses, as agronomic indicators of quality. The low and high clay content were grouped into clusters I and III, respectively, according to the agronomic traits of the peanut crop. The principal components analysis (PC) allowed a single distribution of accesses since only two eigenvalues were higher than “one”: the highest eigenvalues of 4.51 and 1.79, resulted in a Biplot that explained 70% of the original variability, 50.11% and 19.89% of which in the PC1 and PC2, respectively. The multivariate analysis indicated that high peanut yields in soils with low clay are correlated with the losses during the peanut mechanized harvesting operation.
publishDate 2018
dc.date.none.fl_str_mv 2018-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200244
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000200244
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4430-eng.agric.v38n2p244-250/2018
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
publisher.none.fl_str_mv Associação Brasileira de Engenharia Agrícola
dc.source.none.fl_str_mv Engenharia Agrícola v.38 n.2 2018
reponame:Engenharia Agrícola
instname:Associação Brasileira de Engenharia Agrícola (SBEA)
instacron:SBEA
instname_str Associação Brasileira de Engenharia Agrícola (SBEA)
instacron_str SBEA
institution SBEA
reponame_str Engenharia Agrícola
collection Engenharia Agrícola
repository.name.fl_str_mv Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)
repository.mail.fl_str_mv revistasbea@sbea.org.br||sbea@sbea.org.br
_version_ 1752126273668251648